Group 26 - Assignment 5
Carl Felix Freiesleben - s203521
Judith Tierno Martí - s222869
Introduction
The analysis was performed on the dataset: Right Heart Catheterization (RHC) Dataset, first analysed Connors (et. al) (1996)
Before cleaning and augmentation:
5735 patiens
62 attributes
After cleaning and augmentation:
5612 patiens
53 attributes
Contains patient-, socioeconomic-, physiological-, disease-, and survival information.
Materials and Methods
We performed our analysis using \(\color{red}{\text{Tidyverse}}\).
Materials and Methods (exploratory dataviz)
Table 1
rhc_aug |> mutate(sex = factor(sex),
swang1 = factor(swang1),
death = factor(x = death, levels = c(0,1), c("Alive","Dead"))) |>
table1(x = formula(~ sex + age + race + swang1 | death),
data = _)
|
Alive
(N=1972) |
Dead
(N=3640) |
Overall
(N=5612) |
| sex |
|
|
|
| Female |
906 (45.9%) |
1594 (43.8%) |
2500 (44.5%) |
| Male |
1066 (54.1%) |
2046 (56.2%) |
3112 (55.5%) |
| age |
|
|
|
| Mean (SD) |
56.6 (17.4) |
64.0 (15.7) |
61.4 (16.7) |
| Median [Min, Max] |
58.0 [18.0, 102] |
66.0 [18.0, 101] |
64.0 [18.0, 102] |
| race |
|
|
|
| black |
323 (16.4%) |
577 (15.9%) |
900 (16.0%) |
| other |
121 (6.1%) |
223 (6.1%) |
344 (6.1%) |
| white |
1528 (77.5%) |
2840 (78.0%) |
4368 (77.8%) |
| swang1 |
|
|
|
| 0 |
1291 (65.5%) |
2177 (59.8%) |
3468 (61.8%) |
| 1 |
681 (34.5%) |
1463 (40.2%) |
2144 (38.2%) |
Investigating the mean blood pressure of the patients admitted with different diseases
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::: {.column width=“50%”} Violin plot \(\rightarrow\) Multimodal / Bimodal distribution
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Plots
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Modelling
More beautiful plots by Emilie
Discussion
How come we found no major discoveries?
What could have been done differently?
Conclusion
We can conclude that PC can make sense for further analysis.
We can conclude that high values of APS for several diagnosis, will increase the risk of death
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